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Record W2130926269 · doi:10.1139/f08-024

Genetic and environmental implications of reintroducing laboratory-raised unionid mussels to the wild

2008· article· en· W2130926269 on OpenAlexafffundvenue
Eileen Hoftyzer, Josef Daniel Ackerman, Todd J. Morris, Gerald L. Mackie

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsUniversity of GuelphFisheries and Oceans Canada
FundersNatural Sciences and Engineering Research Council of CanadaWorld Wildlife Fund
KeywordsBiologyEcologyEndangered speciesPredationExtinction (optical mineralogy)Captive breedingUnionidaeFreshwater bivalveIntroduced speciesZoologyMolluscaHabitatBivalvia

Abstract

fetched live from OpenAlex

The reintroduction of endangered species is a potentially useful conservation strategy, which in the case of freshwater unionid mussels, must be preceded by the successful laboratory rearing of juvenile mussels on their host fishes. However, an understanding of the genetic and environmental implications of reintroductions of artificially propagated mussels is required. Unfortunately, there is a dearth of information on these issues with respect to freshwater mussels. In general, regarding the genetic effects of reintroductions, small founder populations may lead to low heterozygosity (reduced genetic variability) in the reintroduced populations, which can make them more susceptible to extinction. Captive breeding programs may also alter the genetic composition of species through artificial selection, whether intentional or unintentional. Captive breeding may also affect an individual’s interactions with conspecifics or predators by altering behaviour. Genetic problems in reintroduced populations also have the potential to affect wild populations, particularly by reducing variability among populations of the same species and eliminating local adaptation. There is also the possibility that diseases, parasites, or exotic species may be spread when populations are relocated or augmented. Recommendations related to the minimization of these impacts are presented for freshwater mussels, with the recognition that many of the issues will require additional study.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.197
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations46
Published2008
Admission routes3
Has abstractyes

Explore more

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